Datasets:

kasys
/

ReCaRe

@@ -97,7 +97,7 @@ configs:
 <!-- Provide a quick summary of the dataset. -->
 ReCaRe (pronounced "re-care") is a bilingual legal benchmark for **Revision
-Candidate Retrieval (RCR)** --- locating the provisions of a legal corpus
 that constitute plausible candidates for an authoritative revision. It
 spans European Union law (EUR-Lex, English) and Japanese law (e-Gov,
 Japanese), with 703 amendment events and ~181k articles, supporting two
@@ -113,8 +113,8 @@ Document corpora in regulated domains evolve: statutes are amended, internal
 policies revised, software specifications updated. Yet most information
 retrieval research has framed retrieval as a one-shot question-answering
 problem over a frozen corpus, leaving the IR aspects of *document
-maintenance* --- finding which documents need to change, and which other
-documents must change with them --- comparatively underexplored.
 ReCaRe formalizes two complementary RCR tasks over bilingual corpora of EU and Japanese law:
@@ -159,7 +159,7 @@ ReCaRe is **not** designed for, and should not be used as, a basis for:
   production legal workflow without expert review. Retrieved articles are
   *candidates* for expert review, not authoritative outputs.
 - Provision of legal advice to end-users.
-- Inference of personal or demographic information about individuals --- the
   data contains only public legal text, but personal names appearing in
   legal records (e.g. drafters, ministers) should not be used to build
   profiles of those individuals.
@@ -205,7 +205,7 @@ amending act. The metadata configs are provided for downstream provenance
 analyses and are not required to run the retrieval tasks themselves.
 **Splits.** The `qrels-*` configs use train / validation / test splits. The
-`corpus-*`, `queries-*`, and `metadata-*` configs are not split --- the full
 corpus is used at retrieval time, and queries split membership is encoded
 through the qrels.
@@ -227,7 +227,7 @@ qrels   = load_dataset("kasys/ReCaRe", "qrels-rat2rev-en")  # train/validation/t
 Existing legal-IR benchmarks (e.g. COLIEE, BSARD, LeCaRD, STARD,
 LegalBench-RAG) cover statutory or case-law question answering but not
-*document maintenance* --- finding which provisions must change when a
 corpus evolves. ReCaRe was constructed to give the IR community a shared,
 bilingual benchmark for two practically motivated retrieval tasks
 (Rat2Rev, Rev2Rev) over legal corpora, in two jurisdictions whose

 <!-- Provide a quick summary of the dataset. -->
 ReCaRe (pronounced "re-care") is a bilingual legal benchmark for **Revision
+Candidate Retrieval (RCR)** — locating the provisions of a legal corpus
 that constitute plausible candidates for an authoritative revision. It
 spans European Union law (EUR-Lex, English) and Japanese law (e-Gov,
 Japanese), with 703 amendment events and ~181k articles, supporting two
 policies revised, software specifications updated. Yet most information
 retrieval research has framed retrieval as a one-shot question-answering
 problem over a frozen corpus, leaving the IR aspects of *document
+maintenance* — finding which documents need to change, and which other
+documents must change with them — comparatively underexplored.
 ReCaRe formalizes two complementary RCR tasks over bilingual corpora of EU and Japanese law:
   production legal workflow without expert review. Retrieved articles are
   *candidates* for expert review, not authoritative outputs.
 - Provision of legal advice to end-users.
+- Inference of personal or demographic information about individuals — the
   data contains only public legal text, but personal names appearing in
   legal records (e.g. drafters, ministers) should not be used to build
   profiles of those individuals.
 analyses and are not required to run the retrieval tasks themselves.
 **Splits.** The `qrels-*` configs use train / validation / test splits. The
+`corpus-*`, `queries-*`, and `metadata-*` configs are not split — the full
 corpus is used at retrieval time, and queries split membership is encoded
 through the qrels.
 Existing legal-IR benchmarks (e.g. COLIEE, BSARD, LeCaRD, STARD,
 LegalBench-RAG) cover statutory or case-law question answering but not
+*document maintenance* — finding which provisions must change when a
 corpus evolves. ReCaRe was constructed to give the IR community a shared,
 bilingual benchmark for two practically motivated retrieval tasks
 (Rat2Rev, Rev2Rev) over legal corpora, in two jurisdictions whose